Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models

We use monthly data on the US riskless yield curve for a 1982-2015 sample to show that mixing simple regime switching dynamics with Nelson-Siegel factor forecasts from time series models extended to encompass variables that summarize the state of monetary policy, leads to superior predictive accuracy. Such spread in forecasting power turns out to be statistically significant even controlling for parameter uncertainty and sample variation. Exploiting regimes, we obtain evidence that the increase in predictive accuracy is stronger during the Great Financial Crisis in 2007-2009, when monetary policy underwent a significant, sudden shift. Although more caution applies when transaction costs are accounted for, we also report that the increase in predictive power owed to the combination of regimes and of monetary variables that capture the stance of unconventional monetary policies is tradeable. We devise and test butterfly strategies that trade on the basis of the forecasts from the models and obtain evidence of riskadjusted profits both per se and in comparisons to simpler models.